{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Developer Salary in China 全国程序员工资调查\n",
    "我在4月1日到3日之间，抓取了某招聘网站的软件和互联网类招聘数据40万条，其中通过程序判断为程序员的14万条。地域方面，我选择了24个主要城市。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import db\n",
    "import inspect\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import scipy.stats as stats\n",
    "import numpy as np\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "conn=db.get_conn()\n",
    "data_original=pd.read_sql(sql=\"select * from _201904 where monthly_salary>0 and monthly_salary<15\", con=conn)\n",
    "conn.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "error_job_ids=['104660258','104142922','108434795','101357291','106253516','110368302','111391233','108665401','109277048'\n",
    "                  ,'73857191','108584955','102824950','102824949','111391233','110884556']\n",
    "data=data_original[~data_original.job_id.isin(error_job_ids)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "del data['publish_date']\n",
    "del data['published_on_weekend']\n",
    "del data['title']\n",
    "del data['company_title']\n",
    "del data['company_description']\n",
    "del data['job_description']\n",
    "del data['job_id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Unilateral Stats 总体统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "有数据可知，程序员向一线城市集中的趋势非常明显。\n",
    "\n",
    "According to the statistics, significant amount of developers are in the first tier cities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2019年中国大陆一二线城市程序员的平均工资为13756元，工资中位数为12500元，其中95%的人的工资位于3750到33333元之间。\n"
     ]
    }
   ],
   "source": [
    "salary_mean=data.monthly_salary.mean()*10000\n",
    "salary_median=data.monthly_salary.median()*10000\n",
    "q=np.quantile(data.monthly_salary,[0.025,0.975])*10000\n",
    "print('2019年中国大陆一二线城市程序员的平均工资为{:.0f}元，工资中位数为{:.0f}元，其中95%的人的工资位于{:.0f}到{:.0f}元之间。'\n",
    "      .format(salary_mean, salary_median, q[0], q[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "In 2019, Developers in China earn 13756 Yuan as average, the median is 12500 Yuan, 95% of them earn between 3750 and 33333 Yuan.\n"
     ]
    }
   ],
   "source": [
    "print('In 2019, Developers in China earn {:.0f} Yuan as average, '\n",
    "      'the median is {:.0f} Yuan, 95% of them earn between {:.0f} and {:.0f} Yuan.'\n",
    "      .format(salary_mean, salary_median, q[0], q[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1f7c0716748>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.monthly_salary.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It does not look like normal distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy import stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NormaltestResult(statistic=80485.89395778668, pvalue=0.0)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.normaltest(data.monthly_salary)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "null hypothesis: x comes from a normal distribution\n",
    "    \n",
    "p=0\n",
    "\n",
    "The null hypothesis can be rejected\n",
    "\n",
    "conclusion: data is not normally distributed."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Zoom in"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data[data.monthly_salary<4].monthly_salary.hist()\n",
    "plt.annotate('https://github.com/juwikuang/china_job_survey', xy=(0,0), xytext=(0.15, 500), color='white')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Role 角色"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_sub_stats(data, prefix):\n",
    "    \n",
    "    features = [feature for feature in data.columns if feature.startswith(prefix)]\n",
    "    salary_mean=[]\n",
    "    salary_median=[]\n",
    "    count=[]\n",
    "    for feature in features:\n",
    "        salary_mean.append(data[data[feature]==1].monthly_salary.mean()*10000)\n",
    "        salary_median.append(data[data[feature]==1].monthly_salary.median()*10000)\n",
    "        count.append(data[data[feature]==1].shape[0])\n",
    "    sub_data=pd.DataFrame()\n",
    "    sub_data[prefix]=[f.replace(prefix,'') for f in features]\n",
    "    sub_data['salary_mean']=salary_mean\n",
    "    sub_data['salary_median']=salary_median\n",
    "    sub_data['head_count']=count\n",
    "    sub_data['percentage']=count/np.sum(count)\n",
    "    sub_data=sub_data.sort_values(by='salary_mean', ascending=False)\n",
    "\n",
    "    return sub_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_category_column(data, prefix):\n",
    "    prefix_=prefix+\"_\"\n",
    "    features = [feature for feature in data.columns if feature.startswith(prefix)]\n",
    "    data.loc[:,prefix]=['']*data.shape[0]\n",
    "    for feature in features:\n",
    "        data.loc[data[feature]==1,prefix]=feature.replace(prefix_,'')\n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"blank level0\" ></th> \n",
       "        <th class=\"col_heading level0 col0\" >career_</th> \n",
       "        <th class=\"col_heading level0 col1\" >salary_mean</th> \n",
       "        <th class=\"col_heading level0 col2\" >salary_median</th> \n",
       "        <th class=\"col_heading level0 col3\" >head_count</th> \n",
       "        <th class=\"col_heading level0 col4\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <th id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031eflevel0_row0\" class=\"row_heading level0 row0\" >1</th> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow0_col0\" class=\"data row0 col0\" >architect</td> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow0_col1\" class=\"data row0 col1\" >21490.6</td> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow0_col2\" class=\"data row0 col2\" >20000</td> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow0_col3\" class=\"data row0 col3\" >6233</td> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow0_col4\" class=\"data row0 col4\" >4.36%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031eflevel0_row1\" class=\"row_heading level0 row1\" >0</th> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow1_col0\" class=\"data row1 col0\" >algorithm</td> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow1_col1\" class=\"data row1 col1\" >20312</td> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow1_col2\" class=\"data row1 col2\" >18000</td> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow1_col3\" class=\"data row1 col3\" >15821</td> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow1_col4\" class=\"data row1 col4\" >11.06%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031eflevel0_row2\" class=\"row_heading level0 row2\" >3</th> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow2_col0\" class=\"data row2 col0\" >spider</td> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow2_col1\" class=\"data row2 col1\" >13876.9</td> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow2_col2\" class=\"data row2 col2\" >12500</td> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow2_col3\" class=\"data row2 col3\" >297</td> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow2_col4\" class=\"data row2 col4\" >0.21%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031eflevel0_row3\" class=\"row_heading level0 row3\" >2</th> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow3_col0\" class=\"data row3 col0\" >software_engineer</td> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow3_col1\" class=\"data row3 col1\" >12817.3</td> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow3_col2\" class=\"data row3 col2\" >12500</td> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow3_col3\" class=\"data row3 col3\" >120746</td> \n",
       "        <td id=\"T_bfbad1fa_59bd_11e9_83ec_701ce71031efrow3_col4\" class=\"data row3 col4\" >84.38%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1f798616748>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_career=get_sub_stats(data,'career_')\n",
    "data_career.style.format({\"percentage\":\"{:.2%}\"})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "有表可知，架构师的工资平均为2.1万，算法工程师为2万，普通程序员为1万3。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "F_onewayResult(statistic=15108.459348816918, pvalue=0.0)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "career_architect_salary=data[data.career_architect==1].monthly_salary\n",
    "career_algorithm_salary=data[data.career_algorithm==1].monthly_salary\n",
    "career_software_engineer_salary=data[data.career_software_engineer==1].monthly_salary\n",
    "stats.f_oneway(career_algorithm_salary, career_software_engineer_salary)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "F_onewayResult(statistic=50.85401453755663, pvalue=1.0257032259318573e-12)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.f_oneway(career_architect_salary, career_algorithm_salary)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "统计表面，架构师，算法工程师，普通程序员之间的平均工资差异是显著的。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 编程语言"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"blank level0\" ></th> \n",
       "        <th class=\"col_heading level0 col0\" >pl_</th> \n",
       "        <th class=\"col_heading level0 col1\" >salary_mean</th> \n",
       "        <th class=\"col_heading level0 col2\" >salary_median</th> \n",
       "        <th class=\"col_heading level0 col3\" >head_count</th> \n",
       "        <th class=\"col_heading level0 col4\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row0\" class=\"row_heading level0 row0\" >7</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow0_col0\" class=\"data row0 col0\" >java</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow0_col1\" class=\"data row0 col1\" >14155.7</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow0_col2\" class=\"data row0 col2\" >12500</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow0_col3\" class=\"data row0 col3\" >53327</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow0_col4\" class=\"data row0 col4\" >29.28%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row1\" class=\"row_heading level0 row1\" >2</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow1_col0\" class=\"data row1 col0\" >cpp</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow1_col1\" class=\"data row1 col1\" >15869.1</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow1_col2\" class=\"data row1 col2\" >14000</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow1_col3\" class=\"data row1 col3\" >29281</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow1_col4\" class=\"data row1 col4\" >16.08%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row2\" class=\"row_heading level0 row2\" >8</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow2_col0\" class=\"data row2 col0\" >javascript</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow2_col1\" class=\"data row2 col1\" >12274.7</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow2_col2\" class=\"data row2 col2\" >11500</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow2_col3\" class=\"data row2 col3\" >27483</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow2_col4\" class=\"data row2 col4\" >15.09%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row3\" class=\"row_heading level0 row3\" >1</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow3_col0\" class=\"data row3 col0\" >c_sharp</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow3_col1\" class=\"data row3 col1\" >12008.1</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow3_col2\" class=\"data row3 col2\" >11500</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow3_col3\" class=\"data row3 col3\" >19954</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow3_col4\" class=\"data row3 col4\" >10.96%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row4\" class=\"row_heading level0 row4\" >16</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow4_col0\" class=\"data row4 col0\" >python</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow4_col1\" class=\"data row4 col1\" >17751.1</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow4_col2\" class=\"data row4 col2\" >15000</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow4_col3\" class=\"data row4 col3\" >14946</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow4_col4\" class=\"data row4 col4\" >8.21%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row5\" class=\"row_heading level0 row5\" >4</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow5_col0\" class=\"data row5 col0\" >go</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow5_col1\" class=\"data row5 col1\" >17567.8</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow5_col2\" class=\"data row5 col2\" >15000</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow5_col3\" class=\"data row5 col3\" >12630</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow5_col4\" class=\"data row5 col4\" >6.94%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row6\" class=\"row_heading level0 row6\" >15</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow6_col0\" class=\"data row6 col0\" >php</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow6_col1\" class=\"data row6 col1\" >13163.2</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow6_col2\" class=\"data row6 col2\" >12000</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow6_col3\" class=\"data row6 col3\" >9457</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow6_col4\" class=\"data row6 col4\" >5.19%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row7\" class=\"row_heading level0 row7\" >12</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow7_col0\" class=\"data row7 col0\" >matlab</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow7_col1\" class=\"data row7 col1\" >17720.6</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow7_col2\" class=\"data row7 col2\" >16000</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow7_col3\" class=\"data row7 col3\" >2691</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow7_col4\" class=\"data row7 col4\" >1.48%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row8\" class=\"row_heading level0 row8\" >11</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow8_col0\" class=\"data row8 col0\" >lua</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow8_col1\" class=\"data row8 col1\" >16210.1</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow8_col2\" class=\"data row8 col2\" >15000</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow8_col3\" class=\"data row8 col3\" >2327</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow8_col4\" class=\"data row8 col4\" >1.28%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row9\" class=\"row_heading level0 row9\" >20</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow9_col0\" class=\"data row9 col0\" >swift</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow9_col1\" class=\"data row9 col1\" >14246.1</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow9_col2\" class=\"data row9 col2\" >12500</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow9_col3\" class=\"data row9 col3\" >1515</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow9_col4\" class=\"data row9 col4\" >0.83%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row10\" class=\"row_heading level0 row10\" >19</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow10_col0\" class=\"data row10 col0\" >scala</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow10_col1\" class=\"data row10 col1\" >20518.4</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow10_col2\" class=\"data row10 col2\" >18500</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow10_col3\" class=\"data row10 col3\" >1443</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow10_col4\" class=\"data row10 col4\" >0.79%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row11\" class=\"row_heading level0 row11\" >14</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow11_col0\" class=\"data row11 col0\" >perl</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow11_col1\" class=\"data row11 col1\" >17219.9</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow11_col2\" class=\"data row11 col2\" >15000</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow11_col3\" class=\"data row11 col3\" >1381</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow11_col4\" class=\"data row11 col4\" >0.76%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row12\" class=\"row_heading level0 row12\" >0</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow12_col0\" class=\"data row12 col0\" >assembly</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow12_col1\" class=\"data row12 col1\" >15411</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow12_col2\" class=\"data row12 col2\" >13000</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow12_col3\" class=\"data row12 col3\" >1095</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow12_col4\" class=\"data row12 col4\" >0.60%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row13\" class=\"row_heading level0 row13\" >21</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow13_col0\" class=\"data row13 col0\" >typescript</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow13_col1\" class=\"data row13 col1\" >14287.9</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow13_col2\" class=\"data row13 col2\" >12500</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow13_col3\" class=\"data row13 col3\" >983</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow13_col4\" class=\"data row13 col4\" >0.54%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row14\" class=\"row_heading level0 row14\" >17</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow14_col0\" class=\"data row14 col0\" >ruby</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow14_col1\" class=\"data row14 col1\" >16159.7</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow14_col2\" class=\"data row14 col2\" >14500</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow14_col3\" class=\"data row14 col3\" >716</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow14_col4\" class=\"data row14 col4\" >0.39%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row15\" class=\"row_heading level0 row15\" >25</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow15_col0\" class=\"data row15 col0\" >r</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow15_col1\" class=\"data row15 col1\" >17300.9</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow15_col2\" class=\"data row15 col2\" >15000</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow15_col3\" class=\"data row15 col3\" >648</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow15_col4\" class=\"data row15 col4\" >0.36%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row16\" class=\"row_heading level0 row16\" >3</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow16_col0\" class=\"data row16 col0\" >delphi</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow16_col1\" class=\"data row16 col1\" >10740.6</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow16_col2\" class=\"data row16 col2\" >10000</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow16_col3\" class=\"data row16 col3\" >562</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow16_col4\" class=\"data row16 col4\" >0.31%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row17\" class=\"row_heading level0 row17\" >24</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow17_col0\" class=\"data row17 col0\" >visual_basic_net</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow17_col1\" class=\"data row17 col1\" >12252.3</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow17_col2\" class=\"data row17 col2\" >10000</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow17_col3\" class=\"data row17 col3\" >556</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow17_col4\" class=\"data row17 col4\" >0.31%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row18\" class=\"row_heading level0 row18\" >10</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow18_col0\" class=\"data row18 col0\" >kotlin</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow18_col1\" class=\"data row18 col1\" >14866.8</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow18_col2\" class=\"data row18 col2\" >12500</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow18_col3\" class=\"data row18 col3\" >412</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow18_col4\" class=\"data row18 col4\" >0.23%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row19\" class=\"row_heading level0 row19\" >13</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow19_col0\" class=\"data row19 col0\" >objective_c</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow19_col1\" class=\"data row19 col1\" >13493</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow19_col2\" class=\"data row19 col2\" >12500</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow19_col3\" class=\"data row19 col3\" >216</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow19_col4\" class=\"data row19 col4\" >0.12%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row20\" class=\"row_heading level0 row20\" >22</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow20_col0\" class=\"data row20 col0\" >vba</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow20_col1\" class=\"data row20 col1\" >11461</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow20_col2\" class=\"data row20 col2\" >11000</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow20_col3\" class=\"data row20 col3\" >204</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow20_col4\" class=\"data row20 col4\" >0.11%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row21\" class=\"row_heading level0 row21\" >18</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow21_col0\" class=\"data row21 col0\" >rust</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow21_col1\" class=\"data row21 col1\" >19343.9</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow21_col2\" class=\"data row21 col2\" >17250</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow21_col3\" class=\"data row21 col3\" >158</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow21_col4\" class=\"data row21 col4\" >0.09%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row22\" class=\"row_heading level0 row22\" >5</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow22_col0\" class=\"data row22 col0\" >groovy</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow22_col1\" class=\"data row22 col1\" >17969.9</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow22_col2\" class=\"data row22 col2\" >16500</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow22_col3\" class=\"data row22 col3\" >83</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow22_col4\" class=\"data row22 col4\" >0.05%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row23\" class=\"row_heading level0 row23\" >23</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow23_col0\" class=\"data row23 col0\" >visual_basic</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow23_col1\" class=\"data row23 col1\" >11034</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow23_col2\" class=\"data row23 col2\" >11500</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow23_col3\" class=\"data row23 col3\" >27</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow23_col4\" class=\"data row23 col4\" >0.01%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row24\" class=\"row_heading level0 row24\" >6</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow24_col0\" class=\"data row24 col0\" >haskell</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow24_col1\" class=\"data row24 col1\" >24371.8</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow24_col2\" class=\"data row24 col2\" >22500</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow24_col3\" class=\"data row24 col3\" >13</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow24_col4\" class=\"data row24 col4\" >0.01%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031eflevel0_row25\" class=\"row_heading level0 row25\" >9</th> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow25_col0\" class=\"data row25 col0\" >julia</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow25_col1\" class=\"data row25 col1\" >14383.3</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow25_col2\" class=\"data row25 col2\" >14000</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow25_col3\" class=\"data row25 col3\" >5</td> \n",
       "        <td id=\"T_c9ceab64_59bd_11e9_a7b7_701ce71031efrow25_col4\" class=\"data row25 col4\" >0.00%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1f79f19fb00>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_pl=get_sub_stats(data,'pl_')\n",
    "data_pl.sort_values(by='head_count',ascending=False).style.format({\"percentage\":\"{:.2%}\"})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数据显示，haskell才是最赚钱的编程语言。python是主流语言里面最赚钱的，比java的工资多了3000元！vb是最不赚钱的了。其中，最赚钱的编程语言和最不赚钱的，工资居然差了2倍。所以，要选好编程语言呀！"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 教育"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_d8a33298_59bd_11e9_861a_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"blank level0\" ></th> \n",
       "        <th class=\"col_heading level0 col0\" >edu_</th> \n",
       "        <th class=\"col_heading level0 col1\" >salary_mean</th> \n",
       "        <th class=\"col_heading level0 col2\" >salary_median</th> \n",
       "        <th class=\"col_heading level0 col3\" >head_count</th> \n",
       "        <th class=\"col_heading level0 col4\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <th id=\"T_d8a33298_59bd_11e9_861a_701ce71031eflevel0_row0\" class=\"row_heading level0 row0\" >5</th> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow0_col0\" class=\"data row0 col0\" >phd</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow0_col1\" class=\"data row0 col1\" >29591.5</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow0_col2\" class=\"data row0 col2\" >25000</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow0_col3\" class=\"data row0 col3\" >174</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow0_col4\" class=\"data row0 col4\" >0.15%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_d8a33298_59bd_11e9_861a_701ce71031eflevel0_row1\" class=\"row_heading level0 row1\" >3</th> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow1_col0\" class=\"data row1 col0\" >master</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow1_col1\" class=\"data row1 col1\" >20689.4</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow1_col2\" class=\"data row1 col2\" >18000</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow1_col3\" class=\"data row1 col3\" >3591</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow1_col4\" class=\"data row1 col4\" >3.10%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_d8a33298_59bd_11e9_861a_701ce71031eflevel0_row2\" class=\"row_heading level0 row2\" >1</th> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow2_col0\" class=\"data row2 col0\" >bachelor</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow2_col1\" class=\"data row2 col1\" >15020.8</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow2_col2\" class=\"data row2 col2\" >12500</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow2_col3\" class=\"data row2 col3\" >72031</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow2_col4\" class=\"data row2 col4\" >62.14%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_d8a33298_59bd_11e9_861a_701ce71031eflevel0_row3\" class=\"row_heading level0 row3\" >0</th> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow3_col0\" class=\"data row3 col0\" >associate</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow3_col1\" class=\"data row3 col1\" >11137.1</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow3_col2\" class=\"data row3 col2\" >10000</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow3_col3\" class=\"data row3 col3\" >39624</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow3_col4\" class=\"data row3 col4\" >34.18%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_d8a33298_59bd_11e9_861a_701ce71031eflevel0_row4\" class=\"row_heading level0 row4\" >4</th> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow4_col0\" class=\"data row4 col0\" >middle_school</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow4_col1\" class=\"data row4 col1\" >9396.55</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow4_col2\" class=\"data row4 col2\" >7000</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow4_col3\" class=\"data row4 col3\" >58</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow4_col4\" class=\"data row4 col4\" >0.05%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_d8a33298_59bd_11e9_861a_701ce71031eflevel0_row5\" class=\"row_heading level0 row5\" >2</th> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow5_col0\" class=\"data row5 col0\" >high_school</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow5_col1\" class=\"data row5 col1\" >8333.78</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow5_col2\" class=\"data row5 col2\" >7000</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow5_col3\" class=\"data row5 col3\" >448</td> \n",
       "        <td id=\"T_d8a33298_59bd_11e9_861a_701ce71031efrow5_col4\" class=\"data row5 col4\" >0.39%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1f793ea5550>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_edu=get_sub_stats(data,'edu_')\n",
    "data_edu.style.format({\"percentage\":\"{:.2%}\"})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "大专，本科，硕士，博士的平均工资分别是12828，16840，23084，30308。中位数分别是12500， 15000，21000， 29000。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "salary_phd=data[data.edu_phd==1].monthly_salary * 10000\n",
    "salary_master=data[data.edu_master==1].monthly_salary * 10000\n",
    "salary_bachelor=data[data.edu_bachelor==1].monthly_salary * 10000\n",
    "salary_associate=data[data.edu_associate==1].monthly_salary * 10000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "大专，本科，硕士，博士的平均工资分别是11137，15021，20689，29591。中位数分别是10000， 12500，18000， 25000。\n"
     ]
    }
   ],
   "source": [
    "print('大专，本科，硕士，博士的平均工资分别是{:.0f}，{:.0f}，{:.0f}，{:.0f}。中位数分别是{:.0f}， {:.0f}，{:.0f}， {:.0f}。'.format(\n",
    "    salary_associate.mean(),salary_bachelor.mean(),salary_master.mean(),salary_phd.mean(),\n",
    "    salary_associate.median(),salary_bachelor.median(),salary_master.median(),salary_phd.median()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "F_onewayResult(statistic=99.52151746106234, pvalue=3.7529701049822114e-23)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.f_oneway(salary_phd, salary_master)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "F_onewayResult(statistic=1688.374319851099, pvalue=0.0)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.f_oneway(salary_master, salary_bachelor)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "F_onewayResult(statistic=7542.405799147878, pvalue=0.0)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.f_oneway(salary_bachelor, salary_associate)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "经过Oneway Anova Test，证明从大专到博士，学历每提高一级，工资都有显著的提高。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:362: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self.obj[key] = _infer_fill_value(value)\n",
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:543: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self.obj[item] = s\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data=add_category_column(data,'edu')\n",
    "order=['phd','master','bachelor','associate']\n",
    "a=sns.boxplot(y='edu',x='monthly_salary',order=order,data=data[data.edu.isin(order)], orient='h')\n",
    "plt.annotate('https://github.com/juwikuang/job_survey', xy=(0.5,1.5), xytext=(2, 1.55))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 工作经验 Working Experience"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_df639d30_59bd_11e9_9913_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"blank level0\" ></th> \n",
       "        <th class=\"col_heading level0 col0\" >experience_</th> \n",
       "        <th class=\"col_heading level0 col1\" >salary_mean</th> \n",
       "        <th class=\"col_heading level0 col2\" >salary_median</th> \n",
       "        <th class=\"col_heading level0 col3\" >head_count</th> \n",
       "        <th class=\"col_heading level0 col4\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <th id=\"T_df639d30_59bd_11e9_9913_701ce71031eflevel0_row0\" class=\"row_heading level0 row0\" >0</th> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow0_col0\" class=\"data row0 col0\" >10</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow0_col1\" class=\"data row0 col1\" >29943.1</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow0_col2\" class=\"data row0 col2\" >27500</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow0_col3\" class=\"data row0 col3\" >472</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow0_col4\" class=\"data row0 col4\" >0.34%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_df639d30_59bd_11e9_9913_701ce71031eflevel0_row1\" class=\"row_heading level0 row1\" >3</th> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow1_col0\" class=\"data row1 col0\" >5_10</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow1_col1\" class=\"data row1 col1\" >20636</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow1_col2\" class=\"data row1 col2\" >19000</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow1_col3\" class=\"data row1 col3\" >17281</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow1_col4\" class=\"data row1 col4\" >12.38%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_df639d30_59bd_11e9_9913_701ce71031eflevel0_row2\" class=\"row_heading level0 row2\" >2</th> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow2_col0\" class=\"data row2 col0\" >3_5</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow2_col1\" class=\"data row2 col1\" >15022</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow2_col2\" class=\"data row2 col2\" >12500</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow2_col3\" class=\"data row2 col3\" >40163</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow2_col4\" class=\"data row2 col4\" >28.78%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_df639d30_59bd_11e9_9913_701ce71031eflevel0_row3\" class=\"row_heading level0 row3\" >4</th> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow3_col0\" class=\"data row3 col0\" >no</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow3_col1\" class=\"data row3 col1\" >11874.3</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow3_col2\" class=\"data row3 col2\" >10416.7</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow3_col3\" class=\"data row3 col3\" >38124</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow3_col4\" class=\"data row3 col4\" >27.32%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_df639d30_59bd_11e9_9913_701ce71031eflevel0_row4\" class=\"row_heading level0 row4\" >1</th> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow4_col0\" class=\"data row4 col0\" >1_3</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow4_col1\" class=\"data row4 col1\" >11328.5</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow4_col2\" class=\"data row4 col2\" >10416.7</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow4_col3\" class=\"data row4 col3\" >43526</td> \n",
       "        <td id=\"T_df639d30_59bd_11e9_9913_701ce71031efrow4_col4\" class=\"data row4 col4\" >31.19%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1f79f2a4940>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_experience=get_sub_stats(data,'experience_')\n",
    "data_experience.style.format({\"percentage\":\"{:.2%}\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "salary_we_10=data[data.experience_10==1].monthly_salary * 10000\n",
    "salary_we_5_10=data[data.experience_5_10==1].monthly_salary * 10000\n",
    "salary_we_3_5=data[data.experience_3_5==1].monthly_salary * 10000\n",
    "salary_we_1_3=data[data.experience_1_3==1].monthly_salary * 10000\n",
    "salary_we_no=data[data.experience_no==1].monthly_salary * 10000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data=add_category_column(data,'experience')\n",
    "order=['10','5_10','3_5','1_3']\n",
    "sns.boxplot(y='experience',x='monthly_salary',order=order,data=data[data.experience.isin(order)], orient='h')\n",
    "plt.annotate('https://github.com/juwikuang/job_survey', xy=(1.5,1.5), xytext=(1.55, 1.55))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数据显示，工资会随着工作经验的增长而增长。不过，我感觉那些招十年工作经验的，基本上都是架构师等职位。如果你的工作经验是一年的工作经验重复十次，应该拿不到那么高的工资。这个以后我还会仔细分析。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 城市 City"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"blank level0\" ></th> \n",
       "        <th class=\"col_heading level0 col0\" >city_</th> \n",
       "        <th class=\"col_heading level0 col1\" >salary_mean</th> \n",
       "        <th class=\"col_heading level0 col2\" >salary_median</th> \n",
       "        <th class=\"col_heading level0 col3\" >head_count</th> \n",
       "        <th class=\"col_heading level0 col4\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row0\" class=\"row_heading level0 row0\" >0</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow0_col0\" class=\"data row0 col0\" >beijing</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow0_col1\" class=\"data row0 col1\" >17453</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow0_col2\" class=\"data row0 col2\" >15000</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow0_col3\" class=\"data row0 col3\" >13823</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow0_col4\" class=\"data row0 col4\" >9.90%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row1\" class=\"row_heading level0 row1\" >17</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow1_col0\" class=\"data row1 col0\" >shanghai</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow1_col1\" class=\"data row1 col1\" >16626</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow1_col2\" class=\"data row1 col2\" >15000</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow1_col3\" class=\"data row1 col3\" >25888</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow1_col4\" class=\"data row1 col4\" >18.55%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row2\" class=\"row_heading level0 row2\" >19</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow2_col0\" class=\"data row2 col0\" >shenzhen</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow2_col1\" class=\"data row2 col1\" >15631</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow2_col2\" class=\"data row2 col2\" >14000</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow2_col3\" class=\"data row2 col3\" >20757</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow2_col4\" class=\"data row2 col4\" >14.87%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row3\" class=\"row_heading level0 row3\" >9</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow3_col0\" class=\"data row3 col0\" >hangzhou</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow3_col1\" class=\"data row3 col1\" >14977</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow3_col2\" class=\"data row3 col2\" >12500</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow3_col3\" class=\"data row3 col3\" >8690</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow3_col4\" class=\"data row3 col4\" >6.23%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row4\" class=\"row_heading level0 row4\" >8</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow4_col0\" class=\"data row4 col0\" >guangzhou</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow4_col1\" class=\"data row4 col1\" >13032</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow4_col2\" class=\"data row4 col2\" >12000</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow4_col3\" class=\"data row4 col3\" >17068</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow4_col4\" class=\"data row4 col4\" >12.23%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row5\" class=\"row_heading level0 row5\" >14</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow5_col0\" class=\"data row5 col0\" >nanjing</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow5_col1\" class=\"data row5 col1\" >12874</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow5_col2\" class=\"data row5 col2\" >12500</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow5_col3\" class=\"data row5 col3\" >7091</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow5_col4\" class=\"data row5 col4\" >5.08%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row6\" class=\"row_heading level0 row6\" >3</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow6_col0\" class=\"data row6 col0\" >chengdu</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow6_col1\" class=\"data row6 col1\" >11896</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow6_col2\" class=\"data row6 col2\" >11500</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow6_col3\" class=\"data row6 col3\" >7028</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow6_col4\" class=\"data row6 col4\" >5.04%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row7\" class=\"row_heading level0 row7\" >6</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow7_col0\" class=\"data row7 col0\" >dongguan</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow7_col1\" class=\"data row7 col1\" >11353</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow7_col2\" class=\"data row7 col2\" >10417</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow7_col3\" class=\"data row7 col3\" >1632</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow7_col4\" class=\"data row7 col4\" >1.17%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row8\" class=\"row_heading level0 row8\" >22</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow8_col0\" class=\"data row8 col0\" >xian</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow8_col1\" class=\"data row8 col1\" >11075</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow8_col2\" class=\"data row8 col2\" >10000</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow8_col3\" class=\"data row8 col3\" >3833</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow8_col4\" class=\"data row8 col4\" >2.75%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row9\" class=\"row_heading level0 row9\" >21</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow9_col0\" class=\"data row9 col0\" >wuhan</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow9_col1\" class=\"data row9 col1\" >11074</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow9_col2\" class=\"data row9 col2\" >10417</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow9_col3\" class=\"data row9 col3\" >8027</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow9_col4\" class=\"data row9 col4\" >5.75%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row10\" class=\"row_heading level0 row10\" >20</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow10_col0\" class=\"data row10 col0\" >tianjin</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow10_col1\" class=\"data row10 col1\" >10988</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow10_col2\" class=\"data row10 col2\" >10000</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow10_col3\" class=\"data row10 col3\" >1147</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow10_col4\" class=\"data row10 col4\" >0.82%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row11\" class=\"row_heading level0 row11\" >2</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow11_col0\" class=\"data row11 col0\" >changsha</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow11_col1\" class=\"data row11 col1\" >10847</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow11_col2\" class=\"data row11 col2\" >10000</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow11_col3\" class=\"data row11 col3\" >3354</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow11_col4\" class=\"data row11 col4\" >2.40%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row12\" class=\"row_heading level0 row12\" >15</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow12_col0\" class=\"data row12 col0\" >ningbo</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow12_col1\" class=\"data row12 col1\" >10809</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow12_col2\" class=\"data row12 col2\" >10000</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow12_col3\" class=\"data row12 col3\" >1485</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow12_col4\" class=\"data row12 col4\" >1.06%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row13\" class=\"row_heading level0 row13\" >7</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow13_col0\" class=\"data row13 col0\" >fuzhou</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow13_col1\" class=\"data row13 col1\" >10062</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow13_col2\" class=\"data row13 col2\" >9000</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow13_col3\" class=\"data row13 col3\" >2085</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow13_col4\" class=\"data row13 col4\" >1.49%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row14\" class=\"row_heading level0 row14\" >5</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow14_col0\" class=\"data row14 col0\" >dalian</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow14_col1\" class=\"data row14 col1\" >10030</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow14_col2\" class=\"data row14 col2\" >9000</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow14_col3\" class=\"data row14 col3\" >2889</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow14_col4\" class=\"data row14 col4\" >2.07%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row15\" class=\"row_heading level0 row15\" >4</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow15_col0\" class=\"data row15 col0\" >chongqing</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow15_col1\" class=\"data row15 col1\" >10017</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow15_col2\" class=\"data row15 col2\" >9000</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow15_col3\" class=\"data row15 col3\" >2570</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow15_col4\" class=\"data row15 col4\" >1.84%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row16\" class=\"row_heading level0 row16\" >16</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow16_col0\" class=\"data row16 col0\" >qingdao</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow16_col1\" class=\"data row16 col1\" >9549</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow16_col2\" class=\"data row16 col2\" >8750</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow16_col3\" class=\"data row16 col3\" >1385</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow16_col4\" class=\"data row16 col4\" >0.99%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row17\" class=\"row_heading level0 row17\" >12</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow17_col0\" class=\"data row17 col0\" >jinan</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow17_col1\" class=\"data row17 col1\" >9375</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow17_col2\" class=\"data row17 col2\" >8500</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow17_col3\" class=\"data row17 col3\" >1479</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow17_col4\" class=\"data row17 col4\" >1.06%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row18\" class=\"row_heading level0 row18\" >11</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow18_col0\" class=\"data row18 col0\" >hefei</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow18_col1\" class=\"data row18 col1\" >9252</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow18_col2\" class=\"data row18 col2\" >8500</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow18_col3\" class=\"data row18 col3\" >3071</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow18_col4\" class=\"data row18 col4\" >2.20%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row19\" class=\"row_heading level0 row19\" >1</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow19_col0\" class=\"data row19 col0\" >changchun</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow19_col1\" class=\"data row19 col1\" >8580</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow19_col2\" class=\"data row19 col2\" >7000</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow19_col3\" class=\"data row19 col3\" >614</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow19_col4\" class=\"data row19 col4\" >0.44%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row20\" class=\"row_heading level0 row20\" >13</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow20_col0\" class=\"data row20 col0\" >kuming</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow20_col1\" class=\"data row20 col1\" >8458</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow20_col2\" class=\"data row20 col2\" >8000</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow20_col3\" class=\"data row20 col3\" >1011</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow20_col4\" class=\"data row20 col4\" >0.72%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row21\" class=\"row_heading level0 row21\" >23</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow21_col0\" class=\"data row21 col0\" >zhengzhou</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow21_col1\" class=\"data row21 col1\" >8348</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow21_col2\" class=\"data row21 col2\" >7000</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow21_col3\" class=\"data row21 col3\" >2317</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow21_col4\" class=\"data row21 col4\" >1.66%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row22\" class=\"row_heading level0 row22\" >18</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow22_col0\" class=\"data row22 col0\" >shenyang</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow22_col1\" class=\"data row22 col1\" >7851</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow22_col2\" class=\"data row22 col2\" >7000</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow22_col3\" class=\"data row22 col3\" >1452</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow22_col4\" class=\"data row22 col4\" >1.04%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031eflevel0_row23\" class=\"row_heading level0 row23\" >10</th> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow23_col0\" class=\"data row23 col0\" >harbin</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow23_col1\" class=\"data row23 col1\" >6403</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow23_col2\" class=\"data row23 col2\" >5250</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow23_col3\" class=\"data row23 col3\" >870</td> \n",
       "        <td id=\"T_e2ec8cee_59bd_11e9_b6dc_701ce71031efrow23_col4\" class=\"data row23 col4\" >0.62%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1f79f2a4710>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_city=get_sub_stats(data,'city_')\n",
    "data_city.style.format({\"percentage\":\"{:.2%}\",\"salary_mean\":\"{:.0f}\",\"salary_median\":\"{:.0f}\"})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "程序员收入最高的城市分别为：北京，上海，深圳，广州"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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jaFxxxRWUl5fTsWPHqJeNxPbt22le8R/+6PpPjXkzi93dmpRV+z/7W9f/iO9TfhSzOAE+/PDDGqONRDZixAiWLl3a4O2uX7++RjIDSE5OrnX7pKSkMHToUFavXh2QmNPS0lixYkXQZYKta/369UHrXn/99b7kApCens4zzzwDuEeVK1asoKKigpSUFFQ1IN5wMYRrNxFU79vQoUNr7Fg0piFDhkT8/kYjmn421DYRkY2qmlVbvXgfHvwAGCAi94tIb1Xd5ylf7Pm9EUj3vD4OeEFEPgQeAbr4tfOqqu5T1UPAVuAsoBfwmqp+o6oVwAvV1v2Sqlap6lbgFE+ZALNEZAuwGmjrNy8kEblRRIpFpHjPnj2R994E5aSEBe7DlI0pku1TUVHBypUra4wkoxmFhuOfWKpPr1q1ioqKCl8c1eMNF0O4dhNB9b6tXLkyrvHE6v2Npp+NvU3ieu9BVd0mIj2BIcBsEfH29rDn9xF+iHEGsFZVR4pIOrDOr6nDfq+9y0gtq/dfxlt3DHAS0FNVK0SkBGgRQT+eAJ4A90irtvrBtGvXDiBmN4rNzc3lUMmGerdzSssqWqR3jOkNbUeOHBn3wy7RGDhwYExGWqFEOtIaNGhQ0JFWQ0hPT68xIvIaOHBgrSOturSbCKr3bdCgQXGNJy0tLSbvbzT9bOxtEu9zWqfjPuT3LPAQ7kN5oRwHfOl5PTaC5ouAPiJyguew35URLHMc8LUnYfXDPWIzjezUU0+NuK5IbfsmddeqVatay1q3bk1OTk5EcSQlJQV9HUxysntfLSsr8GjJBRdcwL333htQdtNNNwVdV05ODnl5eQHl3gs3gsnOzg6Yvuyyy0LWnTRpUsD0lClTfK/9t0dSUhL33XdfxDGEazcRVO9bTk5OXOOJ5v2NRjT9bOxtEu/Dg12BIhHZDNwHzAxT9wHco7E3gWa1NayqXwKzgHdxH+rbCuwLuxAsALJEpBj3qOvjWntgGlxKSgqtW7eOqO7w4cNrJIxo9jbD1V2+fLkveYB7r3/58uUBdZYsWUKbNm0YPnx42PWISEASqF6/+rmjNWvWAPDwww8HlD/wwAMMGDDAF1dycjJjxozxjUjS0tIQEbKzs2ndujW9evXy9TEtLY2ePXuGjPGee+4JmP7Nb34Tsm6nTp1860xPT6dDhw6+eW3atCE7O9sXR//+/SOOIVy7iaB63yL9nMZKNO9vNKLpZ2Nvk7gmLVV9RVUzVLW7qp6vqsWqmq6qpZ75xara1/P6bVXtpKo/VdXJqpruKZ+nqrf4tTlMVdd5Jp9T1U7AAKAdUOypM1ZVF/ktk+b5XaqqF6pqlqqOU9VzVbXEv45pHJGMtgYOHEhOTg4ZGRkB5Xl5eTUSWefOnTn22GNrtDFt2jRSU1NrlJ988skAvlHNMccc49vrP+GEEwAC/jhzcnJ85Zdddhnjx48H4OKLLwbgjjvuICcnh86dO9O5c2dycnJ8IxtvMmvWzL0v5p8o4YfR1gUXXOAr88blvcx50qRJpKamMn36dDIyMgL2dvPy8khKSopoL7x6TOF41xlsNOR9X7xxRBNDuHYTQfW+xVs02zYa0fSzMbdJXK8ejDUReQh3wmoBrARu0xh3uK5XD+bm5gKxP6cV7ArBaK4enFmcRov082N6TivW28IYk3givXrwqH4IpKreGe8YjDHGNJx4n9MyxhhjImZJyxhjjGNY0jLGGOMYlrSMMcY4xlF9IYaTJNr3UeLJtoUxJhRLWgnCe5m3sW1hjAnNDg8aY4xxDEtaxhhjHMOSljHGGMewpGWMMcYxLGkZY4xxDEtaxhhjHMOSljHGGMeIKGmJyIsiMlRELMkZY4yJm0i/XPw48AsgX0ReAOapqj3V12E+L2vme3aWv8/2ux8+GGxesDY6NXhkxhgTmYiSlqquBlaLyHHA1cAqEfkCmAs8q6oVMYzRNIBwt0ZK3bULgBbt2tXaTqda2jLGmJhS1Yh+gNbAbbgfWb8MuAr4I7Au0jaawk/Pnj01kX366afapUuXGuVPP/20fvnll77pRx55RA8cONBg6x08eLDu2rVLVVWfe+45nTlzZtj6F154oS/eBQsWBMT5q1/9Kqp15+Tk6AsvvBBlxA1n1qxZ+uyzz+rjjz+uBQUF9Wrryy+/1CuvvFJV67YtGlpmZqYePnxYs7Oz9dtvvw1ZL9TnzhgvoFgj+B8b6TmtxcDrQEvgMlUdrqr/p6q3ArUfUzIJb968eezevds3/eijj3Lw4MEGabu8vJxvvvmGtm3bAvDyyy9z6aWXhl3mrbfeAqCkpITnnnuuQeKIl5UrVzJo0CAmTJjA9ddfX6+2Tj/9dBYtWtRAkdVPSUkJbdu2pXnz5qxYsYLjjz8+3iFx5MiReIdgYizSCyueVNXOqjpbVf8FICLHAKhqVsyiMzFx5MgRxo8fT5cuXRg0aBDz58+nuLiYMWPG0L17d/7whz+we/du+vXrR79+/QBIS0vjjjvuIDMzk/79+7Nnzx4A8vPz6dy5MxkZGfz85z8Pur5169bRt29fwD2y37x5M5mZmezZs4eBAweSmZnJTTfdxFlnnUVpaalvfQB33303r7/+Ot27d+eRRx4BYPfu3Vx66aV07NiRu+66y7ce7zIAixYtYuzYsb7p1atX07t3bzp16sTf//73oHE+88wzZGRk0K1bN6677joAPvvsM/r3709GRgb9+/fn888/B2Ds2LHcfPPN9OvXj/bt2/Paa6/xy1/+knPPPTdgvf/5z3/4/vvvOemkk8jLy+Ohhx4CoG/fvhQXFwNQWlpKeno6AEOGDGHLli0A9OjRg+nTpwMwefJknnzySUpKSjjvvPNqxL58+XIuvPBCSktLGTt2bEBi826XsrIy+vfvT2ZmJl27dmXp0qWAO/mce+65AZ+J8vJyADZs2EBGRgYXXnghv/nNbwLWXVhY6Nv5SE9P9713Dz/8MOeddx7nnXcejz76qK9+ZWUlOTk5ZGRkMGrUqLA7RXfffbfvc3XnnXf6tnmwfq1bt45+/fpxzTXX0LVrV37729/ypz/9yVcvLy+POXPmAPDggw9y/vnnk5GRwdSpU33b9g9/+IOv/n333Ud+fn7I2EycRTIcAzZFUmY/zjg82KxZM33vvfdUVfVnP/uZzp8/X/v06aMbNmzw1TvrrLN0z549vmlAn332WVVVnTZtmu+w1GmnnaaHDh1SVfUdHtqwYYPecMMNvmVvvfVWffXVV1VVdePGjXrdddepquqvfvUrnTVrlqqqFhYWKuBbZ2pqqqqqrl27VocOHepr6+mnn9azzz5bv/vuOy0vL9czzzxTP//884BlVFVfeOEFzcnJUVX34cHBgwfrkSNHdNu2bdq2bVstLy8P2C4ffvihdurUybf+vXv3qqrqsGHDdN68eaqq+tRTT+mIESN8bV511VVaVVWlL730krZq1Uq3bNmiR44c0czMTN/2ffHFF3Xy5Mmqqjp16lR98MEHVVUDtveePXv0rLPOUlXV2bNn62OPPab79u3TrKwsHTRokKqq9u3bVz/++OOAw2zew4OLFy/Wiy++WL/55htfbP6HQ73bpaKiQvft2+db549//GOtqqoK+ZlQVe3SpYu++eabqqr629/+NuAQ3/Dhw/WTTz5R1R8+L8XFxXreeedpWVmZ7t+/Xzt37qybNm3STz/9VAF94403VFX1F7/4hW9bVLd3717t1KmTVlVVqeoPn6tQ/Vq7dq22bNlSd+7cqaqqmzZtUpfL5at37rnn6meffaavvPKKjh8/XquqqvTIkSM6dOhQfe211/TTTz/VHj16qKrqkSNHtH379lpaWho0NhM7NMThQRE5VUR6AseKSA8RyfT89MV9qNA40Nlnn0337t0B6NmzJyUlJbUuk5SUxFVXXQXAtddeyxtvvAFARkYGY8aM4dlnnyU52X1dT1ZWFk8++aRv2TfffJOLL74YcB8azM7OBuCNN97wjc4uvfRSTjjhhIji79+/P8cddxwtWrSgc+fOfPbZZ7UuM3r0aJKSkujYsSPt27fn448DL35ds2YNo0aNok2bNgCceOKJALz99ttcc801AFx33XW+fgNcdtlliAhdu3bllFNOoWvXriQlJdGlSxffNvXvbyR69+7N+vXreeONNxg6dChlZWUcPHiQkpISfvKTn9Sov3btWu6//36WL19e6/ZTVe69914yMjIYMGAAX375Jf/+97+B4J+J7777jv3793PRRRcB+LYDwPfff8+uXbto3759wDreeOMNRo4cSWpqKmlpaVxxxRW8/vrrAJxxxhn89Kc/BQI/Q9X96Ec/okWLFowbN47FixfTsmXt/2p69erF2WefDbhHqF9//TW7d+/m/fff54QTTuDMM89k5cqVrFy5kh49epCZmcnHH3/M9u3bSU9Pp3Xr1rz33nu++a1bt651nSY+art6cDAwFmgHPOxXvh+4N0YxmRg75phjfK+bNWvmOxQUDREB3Iel1q9fz7Jly5gxYwYfffSRL3kB7Ny5kzPOOIPmzZsD7vM7L774IoB3xF7v+CsrKwNiAjh06FDQeENNq2qNsmD863jjSEpKCogpKSnJF1NRURGPP/54jXaSk5OpqqqqEev5559PcXEx7du3Z+DAgZSWljJ37lx69uwZNJ727duzc+dOtm3bRlZWVo22VZXvv/8egAULFrBnzx42btxISkoK6enpvnUH+0yEe39ef/11346Iv3DL1PYeeCUnJ1NUVMSrr77K888/z2OPPcaaNWtC9gsgNTU1oI1Ro0axaNEivvrqK9+Okapyzz33cNNNN9VY57hx45g3bx5fffUVv/zlL0P2wcRf2JGWqhaoaj9grKr28/sZrqqLGylG0whatWrF/v37Q05XVVX5zic899xzXHzxxVRVVfHFF1/Qr18/HnjgAb777jvKysoC2vU/77Fv3z4qKyt9e7EXX3wxCxcuBNzJ7Ntvv601rnBOOeUU/vGPf1BVVcWSJUsC5r3wwgtUVVXxySefsHPnzhqjlv79+7Nw4UL27t0LwDfffAPARRddxPPPPw+4/+kH+0cdykcffcQ555xDs2bNasxLT09n48aNAAHnaZo3b84ZZ5zBwoULueCCC+jduzcPPfQQvXv3DrqOs846i8WLF3P99dfz0Ucf1Wh76dKlVFS4v5Gyb98+Tj75ZFJSUli7dm2tI9QTTjiBVq1a8c477wD4tgOEHkG6XC5eeuklDh48yIEDB1iyZIkv9s8//5y3334bgL/+9a8ht2VZWRn79u1jyJAhPProo2zevDlsv4L5+c9/zvPPP8+iRYsYNWoUAIMHD+Yvf/mL7zP65Zdf8vXXXwMwcuRIXn75ZTZs2MDgwYPDbhcTX7UdHrzW8zJdRCZW/2mE+EwjGTt2LBMmTKB79+6Ul5dz4403kp2d7bsQIzU1lY8++oiePXuyZs0apkyZwpEjR7j22mvp2rUrPXr04Ne//jXHH388xcXFjBs3Dgi8UnDVqlUMGDDAt86pU6eycuVKMjMzKSws5LTTTqNVq1YBcWVkZJCcnEy3bt18F2KE8vvf/55hw4ZxySWXcNpppwXM+8lPfkKfPn3Izs7mf//3f2nRogW7d+9myJAhAHTp0oX77ruPPn360K1bNyZOdH+88/Pzefrpp8nIyGD+/PkBJ+xr45+wvbyjizvvvJPHH3+ciy66yHcBg1fv3r055ZRTaNmyJb1792bXrl0hk5a3bwsWLOBnP/sZn3zyCePHj+e1116jV69evPvuu75RyJgxYyguLiYrK4sFCxZwzjnn1NqHp556ihtvvJELL7wQVeW4444D3Bc/9OnTp0bfMjMzGTt2LL169eK//uu/GDduHD169ADg3HPPpaCggIyMDL755htuvvnmoOvcv38/w4YNIyMjgz59+vje91D9CqZLly7s37+ftm3b+j4LgwYN4pprruHCCy+ka9eujBo1yrdD1Lx5c/r168fo0aOD7mSYBBLuhBdwk+f31CA/UyI5adbUfhL9Qoy68r/IIVKHDh1S/+1xww036Ntvvx0wv6KiQlVV33rrLe3WrVv9A00gAwYM0N27d/umb7nlFv3LX/4Sx4iit3//ft/r2bNna25urn7xxRd66aUEU+iEAAAZi0lEQVSX+sorKyv1xBNP1O+//z4eITaII0eOaLdu3XTbtm3xDqXJIsILMcKe01LVP3tetgduU9XvAETkBGBOTLKoqbP8/Hx27NgRdN4uz10v2oW460WHDh3Izc1t0HiOOeYY32XdQMDFGeA+XDR69Giqqqpo3rw5c+fObdD1x9uqVat8rydPnsy7775LXl5e/AKqg+XLlzN79mwqKys566yzmDdvHieddBKFhYW+Ol26dGHcuHGkpKTEMdK627p1K8OGDWPkyJF07Ngx3uGYWohGcDJcRN5T1R61lRnIyspS/3/UjSk3N5f3PnoPgn3H8zvP7xDzenTpYd9NMY1u5MiRfPrppwFl999/v51XaoJEZKNG8L3fSG+YmyQiJ6jqt57GT4xiWdOYjoeqvlU1ipPWuU9fhptnTGOrfsGMMbWJNPHMAd4SkUWAAqOB38UsKmOMMSaISO/y/oyIFAOXAAJcoapbYxqZMcYYU03Eh/g8ScoSlTHGmLixkxnGGGMcw5KWMcYYx7CkZYwxxjEsaRljjHEMS1oJIj8//6j4cu/R0g9jTGKyLwgniFC3X3Kao6UfxpjEZCMtY4wxjmFJyxhjjGNY0jLGGOMYlrSMMcY4hiUtY4wxjmFJyxhjjGPYJe+mQVVUVLBz505cLpev7PTTT2f37t016rZu3Zq9e/cGlB177LGUl5eTmZnJpk2bwq6rRYsWzJo1i4KCAt5//31f+fr16yktLeWKK64A3E9QXrVqFUuWLOGRRx7hyiuvZMmSJcyZM4dWrVpx2223cfjwYSorKxERVJWbb76Zq6++mm3btpGbm8upp55KixYt+N3vfse4cePYu3cvJ598MosWLfKtd9u2bdx222388Y9/pKqqittuu40xY8bwxBNPMG3aNPr16xe2P48++iiLFy9m9OjR3HLLLb7yoqIi7rrrLubMmUPPnj3DthFMNMv796FDhw5Rr6shlJaWMm3aNPLy8mjdunXCtxtvidCvxoyhyYy0RGSsiDwW7ziOdl999RXl5eUBZcESFlAjYQG+ZWtLWACHDh1iypQpbNmypca8goIC3+vDhw8D7qQA8OKLL1JVVcXkyZOZOXMmBw4coLKyEgDvk7wff/xxAGbOnMnBgwfZuXMnW7dupaCgwBf3119/HbBOb1vTp0/3vX7iiScAmDFjRq39Wbx4MQALFy4MKM/Ly/PFWxfRLO/fh3gpKChgy5YtAe9hIrcbb4nQr8aMockkLRN7paWlQRNRLJWVlfkSjZfL5WLp0qUBZX379q1Rr6ysjJKSkpBt5+fn15j/0ksvBUyPGjUKcI9QvHVLSkpqLFdZWcnatWtDrsubUL0ee8y9f1VUVERZWZkv3o0bN4ZsI5holq/eh3h8Uby0tJTCwkJUlcLCwgb7PMWq3XhLhH41dgxS/Q+5QRsXmQyMAb4ASoGNwDDgTlUtFpE2QLGqpotIOjAfSPUsfouqviUifYE8z/Lnedq4VlVVRIYAD3vmbQLaq+owEVkBnO5p52wgF/fDK4cDLYEfA0tU9S5PnFcD93rqLFfV33rKy1Q1zfN6FDBMVceG63NWVpYWFxdHva2uuOIKysvL6dixY9TLem3fvp2yqjKqhlXVmJe0zr1/UtU3yLy/J5GWlFavdQN88cUXR80/g2isX7+e66+/PmwCBEhOTmbNmjVB5/kfTvVvd8iQIb6kA5CWlsaKFSsiji2a5av3IT09nWeeeSbidTWEOXPmsGLFCioqKkhJSWHo0KFMnDgxYduNt0ToV0PFICIbVTWrtnoxG2mJSBZwJdADuAKoLZivgYGqmglcBfjfwK4HcDvQGWgP/FREWgB/BrJV9WLgJG9lVR2iqt2BG4DPAO/ucXdP212Bq0TkDBE5Hbgf91OZuwPni8jlUfb1RhEpFpHiPXv2RLPoUeXbb7+NdwhxU1vCAnyHIKPhn3CCTTfk8tX7EEmfGtqqVauoqKgA3OdHV65cmdDtxlsi9KuxY4jlhRgXA0tVtRxARP5WS/0U4DER6Q4cATr5zStS1V2edjYD6UAZsFNVP/XU+Stwo3cBzyhuPjBaVfeJCMCrqrrPM38rcBbQGlinqns85QsAFz8kulqp6hPAE+AeaUW6nL927doB1Otms7m5ubz35XvRL5gGHdt2rPeNbufMmVPjsFxTkZ6eHtFIK1ppaWk1RkqxWr56H9LT06NaV0MYOHBgwF77oEGDErrdeEuEfjV2DLE8pyUhyiv91tvCr/zXwL+BbrhHZc395h32e30Ed7IN1T4i0gx4Hpiuqh/WtR3APwG1CFnLAJCTkxPvEEJKSor+o+49XxXOySefDMCkSZNqrRvuQgjvlY5eo0ePBtwXUfiL5IIOf9EsX70PU6ZMiWpdDSEnJwfPDiZJSUkN9pmKVbvxlgj9auwYYpm03gAuE5EWIpIGDPWUlwDe6279/yscB/xLVauA64BmtbT/MdDecy4M3If9vH4PbFHV5yOI812gj4i08SS7q4HXPPP+LSLnikgSMDKCtpq0Nm3aNPolt2lpab4/GK/169czYsSIgLJ169bVqJeWlhZ2NJGbm1tj/uWXBx459l7y3qlTJ1/d9PT0GsslJyeHveT99ttvD5j2XvLeq1cv3+goLS0t6kveo1m+eh/iccl7mzZtyM7ORkTIzs5usM9TrNqNt0ToV2PHELOkpaobgGXA+8BioBjYBzwE3CwibwFt/Bb5E5AjIu/gPjR4oJb2y4H/Bl4WkTdwj9L2eWbfCQwSkc2en+Fh2vkXcA+w1hPrJlX1HuO6G/g7sAb4V6R9b8pOPfVUjj322ICy008/PWjdYB9u77KZmZm1rqtFixZMnz6djIyMGvP89/aOOeYY4IfEcOWVV5KUlMSMGTOYNGkSqampvkN33sR28803A+7RR8uWLWnfvj2dO3cmJyfHF7d3lOXlbWvKlCm+1zfe6D5iHcnl5t7RlneU5ZWXl+eLty6iWd6/D/GSk5NDRkZGg++xx6rdeEuEfjVmDLG+ejBNVctEpCWwHrhRVWv/Ak707QvwP8B2VX2kodqvi7pePZibmws0zDmtoFcIhrt6cF0SPdr2aJCHNzZEP4wxTU/crx70eMJz4cQm4MWGTFge4z3tf4T78OKfG7h9Y4wxCSSmt3FS1Wti3P4jQFxHVsYYYxqP3RHDGGOMY1jSMsYY4xiWtIwxxjiGPZokQcTrMRAN7WjphzEmMVnSShDeS8Wd7mjphzEmMdnhQWOMMY5hScsYY4xjWNIyxhjjGJa0jDHGOIYlLWOMMY5hScsYY4xjWNIyxhjjGJa0jDHGOIZ9ufho890Pz86qXg5h5rWNaVTGGNMgLGkdRcLdQmmX7gKgXdt2NWe2tdsvGWOcwZLWUcRuoWSMOdrZOS1jjDGOYUnLGGOMY1jSMsYY4xiWtIwxxjiGJS1jjDGOYUnLGGOMY1jSMsYY4xiWtIwxxjiGfbm4CcjPz2fHjh0BZbt2ee6Q0S7IHTKq6dChg31x2RiTECxpNQE7duzg482bOdWvbL/n93elpWGX/SpmURljTPQsaTURpwI3IL7pp1CoVhaMt54xxiQCO6dljDHGMSxpGWOMcQxLWsYYYxzDkpYxxhjHsKRljDHGMSxpGWOMcQxLWsYYYxzDkpYxxhjHsKSVIPLz88nPz493GI2qKfbZGFM/dkeMBFH93oBNQVPsszGmfmykZYwxxjEsaRljjHEMS1rGGGMcw5KWMcYYx7CkZYwxxjEsaRljjHGMhElaIlIiIm2c2r6pm82bN+NyuXw/l1xyScB0uJ+lS5fSt29fxo4dG1A+f/78GnWLioro06cPLpeL6dOn43K5WLZsGaWlpdx666016o8aNYrS0lImTJjAuHHjGDduHBMmTGDv3r3Mnj0bl8vFgw8+GNAX//KioiL69u1LXl4eLpeLp556yreuvXv3ArB69WpcLhdr164FIDs7G5fLxdChQwPaXbJkiS/ecGUNIVTfgqnen3Dzqve1qQq3zerK+1nbuHFjg7UZrVj0K5SESVrGAFRWVkZc9+GHH6aqqoqdO3cGlM+dO7dG3by8PFTdT2FevXo1AHPmzKGgoIAtW7bUqP/1119TUFDA1q1b2bZtG9u2bWPr1q0UFBRQWFgIwN/+9reAZfzL8/LyqKqqYs2aNQAUFBT41lVQUADArFmzAJgxYwYABw4cAGD//v0B7T766KO+eMOVNYRQfQumen/Czave16Yq3DarK+9nbfLkyQ3WZrRi0a9Q4pK0RCRVRJaLyPsi8qGIXOWZdauIbBKRD0TkHL+6fxGRDSLynoiM8JSPFZHFIvKyiGwXkQc85cNFZLPn558i8qnfquvdvmk4mzdvrtfy3iQUibKysqDL/+1vfwvZztKlS2uUvfTSSwHT3hHJ7Nmza13f0qVLUVUKCwtZsmSJL0FXVlYycODAgLre0daSJUt88akqy5YtC1rWEKr3Idxoq7S0lMLCQl9//Pewq8976aWXAvraVEdb4bZZXRUVFfk+a2VlZXEZbcWiX+FINH/4DbZSkSuBS1V1vGf6OOB9YI6q/lFE/hvIVNVxIjIL2Kqqz4rI8UAR0AP4GTDF8/ow8E/gYlX9wm89C4HXVPV/RKSkodsPJisrS4uLi6PeJldccQXl5eV07Ngx6mVrs337dpIOHOAuxFf2FO73/Qa/smAeQKlKTY1JXPVNWoli/fr1uFyuiOunpKRQWVlZa9Jdv349ffr0Cagn4n6/qpe99tprUUZdU7A+rF+/PmjdOXPmsGLFCioqKkhJSWHo0KFMnDgx6LzqfU1OTvaNQJuScNusroYMGRKwg5SWlsaKFSvqG2pUGqpfIrJRVbNqqxevw4MfAANE5H4R6a2q+zzliz2/NwLpnteDgLtFZDOwDmgBnOmZ96qq7lPVQ8BW4CzvCkTkLqBcVf/Hb70N1r4/EblRRIpFpHjPnj2RbwXTJFVUVEQ8SqxeT1WDljW2VatWUVFRAbj7s3LlypDzqscXzSHgo0m4bVZX1Uf0wUb4sRaLfoUTl3sPquo2EekJDAFmi4i3l4c9v4/4xSbAlar6T/82ROS//OoHLCMi/XGPlKrvOjZI+0H68wTwBLhHWsHq1KZdu3YAMbmBbG5uLt/VcVTTGji+Y8eYxBXN6ORoEulIC9yjqEhGWo1t4MCBAXvXgwYNCjkv2EirKQq3zeoqLS2txkirscWiX+HE65zW6cBBVX0WeAjIDFP9FdznosSzbI9a2j4L+BMwWlXLIwgnqvbN0SUpqX5/ApdddhngvvIvmnXefvvtAWXHHHNMwHSrVq0AatS74447gpY1hOp98PYtmJycHF+yTEpKIicnJ+S8X//61wHLxvOCgXgKt83qKi8vL2A6Hhe6xKJf4cTr8GBXoMhzSO4+YGaYujOAFGCLiHzomQ5nLO4BwhLPxRi1HeCNtn3TQLp3716v5aMZYQTbAxURLrvsspDtjBgxokbZ5ZdfHjD9m9/8BoB77rmn1vWNGDECESE7O5uRI0f6RhzJycmsWrUqoO7y5csBGDlypC8+EWH48OFByxpC9T54+xZMmzZtyM7O9vWndevWIeddfvnlAX3t169fg8TrNOG2WV316tXL91lLS0ujZ8+e9W4zWrHoVzhxSVqq+oqqZqhqd1U9X1WLVTVdVUs984tVta/ndbmq3qSqXVX1PFUd5imfp6q3+LU5TFXXqeo0VW3jabu7qg7xzG+Q9htlAzVh0Rw6mjhxIklJSbRv3z6gfPz48TXq5uXl+f7RDxgwAHCPUHJycsjIyKhR/+STTyYnJ4fOnTvTqVMnOnXqROfOncnJyfGNSKqPRPzL8/LySEpK4pJLLgHce6PedXn3RO+9917gh5FHamoq8MMoy8s7svIfUQUrawih+hZM9f6Em1e9r01VuG1WV97PWjy/ThCLfoUSl6sHj2Z1vXowNzcXiO05rRvqcPXgUyjHd+8es7ggNn02xjhLol89aIwxxkTNkpYxxhjHsKRljDHGMSxpGWOMcQxLWsYYYxyjaX41PQF16NAh3iE0uqbYZ2NM/VjSShDey7+bkqbYZ2NM/djhQWOMMY5hScsYY4xjWNIyxhjjGJa0jDHGOIYlLWOMMY5hScsYY4xjWNIyxhjjGPY9rSbiK354HAnAvzy//ctCLXd8zKIyxpjoWNJqAoLdeaJs1y4Ajm/XLuyyx4dY3hhj4sGSVhNgd54wxhwt7JyWMcYYx7CkZYwxxjEsaRljjHEMS1rGGGMcQ1TDX/JsoiMie4DPolysDVAag3BixUnxOilWsHhjzUnxOilWqH+8Z6nqSbVVsqSVAESkWFWz4h1HpJwUr5NiBYs31pwUr5NihcaL1w4PGmOMcQxLWsYYYxzDklZieCLeAUTJSfE6KVaweGPNSfE6KVZopHjtnJYxxhjHsJGWMcYYx7CkFUcicqmI/FNEdojI3fGOJxwROUNE1orIP0TkIxG5Ld4xRUJEmonIeyLy93jHUhsROV5EFonIx57tfGG8YwpFRH7t+Rx8KCJ/FZEW8Y6pOhH5i4h8LSIf+pWdKCKrRGS75/cJ8YzRK0SsD3o+C1tEZImIJMwDF4LF6zfvThFREWkTi3Vb0ooTEWkG/A+QDXQGrhaRzvGNKqxK4A5VPRe4APhVgsfrdRvwj3gHEaE/AC+r6jlANxI0bhFpC+QCWap6HtAM+Hl8owpqHnBptbK7gVdVtSPwqmc6EcyjZqyrgPNUNQPYBtzT2EGFMY+a8SIiZwADgc9jtWJLWvHTC9ihqjtV9XvgeWBEnGMKSVX/paqbPK/34/6H2ja+UYUnIu2AocCT8Y6lNiLyI8AFPAWgqt+r6nfxjSqsZOBYEUkGWgK74xxPDaq6HvimWvEIoMDzugC4vFGDCiFYrKq6UlUrPZPvAOGfI9SIQmxbgEeAu6CWB/XVgyWt+GkLfOE3vYsETwJeIpIO9ADejW8ktXoU9x9QVbwDiUB7YA/wtOdw5pMikhrvoIJR1S+Bh3DvTf8L2KeqK+MbVcROUdV/gXtHDDg5zvFE6pdAYbyDCEdEhgNfqur7sVyPJa34kSBlCX8pp4ikAS8Ct6vqf+IdTygiMgz4WlU3xjuWCCUDmcDjqtoDOEDiHLoK4DkPNAI4GzgdSBWRa+Mb1dFLRO7DfXh+QbxjCUVEWgL3AVNivS5LWvGzCzjDb7odCXiIxZ+IpOBOWAtUdXG846nFT4HhIlKC+9DrJSLybHxDCmsXsEtVvaPXRbiTWCIaAHyqqntUtQJYDFwU55gi9W8ROQ3A8/vrOMcTlojkAMOAMZrY30/6Me6dmPc9f3PtgE0icmpDr8iSVvxsADqKyNki0hz3iexlcY4pJBER3Odb/qGqD8c7ntqo6j2q2k5V03Fv2zWqmrCjAVX9CvhCRH7iKeoPbI1jSOF8DlwgIi09n4v+JOhFI0EsA3I8r3OApXGMJSwRuRT4LTBcVQ/GO55wVPUDVT1ZVdM9f3O7gEzP57pBWdKKE88J1luAV3D/wS9U1Y/iG1VYPwWuwz1i2ez5GRLvoI4ytwILRGQL0B2YFed4gvKMBhcBm4APcP8fSbi7N4jIX4G3gZ+IyC4RuQH4PTBQRLbjvsrt9/GM0StErI8BrYBVnr+3/41rkH5CxNs4607sEacxxhjzAxtpGWOMcQxLWsYYYxzDkpYxxhjHsKRljDHGMSxpGWOMcQxLWsYYYxzDkpYxDuF5dMl/+033DfXIFRFZJyJZMY5nnoiMiuU6jKnOkpYxznE88N+11kpQnjvCG1MvlrSMiQERSfc8wO9Jz4MSF4jIABF50/MAwl6eBxK+5HnI3zsikuFZNs/zkL11IrJTRHI9zf4e+LHn7ggPesrS/B4cucBzWyX/OG4QkUf8pseLSNDbcIlIqogsF5H3PTFf5SmfIiIbPGVPVF9HuDqePswSkdeA+0TkU889LBGRH4lIiXfamEhY0jImdjrgfrBjBnAOcA1wMXAncC8wDXjP85C/e4Fn/JY9BxiM+7lrUz3/2O8GPlHV7qr6G0+9HsDtuB8k2h737bb8PY/7xsHexPAL4OkQ8V4K7FbVbp6HO77sKX9MVc/3lB2L+wau1YWrc7yq9lHVacA63M84A/c9IV/03HTXmIhY0jImdj713Ei0CvgI9xNzFff9+tJxJ7D5AKq6BmgtIsd5ll2uqodVtRT3nchPCbGOIlXd5VnHZk+7Pqp6AFgDDBORc4AUVf0gRFsfAANE5H4R6a2q+zzl/UTkXRH5ALgE6BJk2XB1/s/v9ZO4EyeET6DGBGVJy5jYOez3uspvugr387PCPVPNf9kjnvq1rSNUvSeBsdSSJFR1G9ATd/Ka7Tnk1wL4EzBKVbsCc4EW/stFUOeA3zreBNJFpA/QTFU/DBWPMcFY0jImftYDY8B9JSBQWsuDNffjvut3VDx3ZT8D9+HJv4aqJyKnAwdV9VncTybO5IfkU+p5AGiwqwUjqePvGU8cNsoyUbOreYyJnzzgac+jSA7yw3OeglLVvZ4LOT7E/ej15VGsayHQXVW/DVOnK/CgiFQBFcDNqvqdiMzFPfoqwf0cuOpx1VqnmgXATMIkUGNCsUeTGNMEeL7P9YiqvpoAsYwCRqjqdfGOxTiPjbSMOYqJyPFAEfB+giSsPwLZgD1A1NSJjbSMaWJEpDUQLIH1V9W9jR2PMdGwpGWMMcYx7OpBY4wxjmFJyxhjjGNY0jLGGOMYlrSMMcY4hiUtY4wxjvH/d4pjTKs92DIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data=add_category_column(data,'city')\n",
    "#order=['shenzhen','guangzhou','shanghai','beijing']\n",
    "order=['beijing','shanghai','guangzhou','shenzhen']\n",
    "\n",
    "sns.boxplot(y='city',x='monthly_salary',order=order,data=data[data.city.isin(order)], orient='h')\n",
    "plt.annotate('https://github.com/juwikuang/job_survey', xy=(0.5,1.5), xytext=(1.2, 1.55))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"blank level0\" ></th> \n",
       "        <th class=\"col_heading level0 col0\" >city_</th> \n",
       "        <th class=\"col_heading level0 col1\" >salary_mean</th> \n",
       "        <th class=\"col_heading level0 col2\" >salary_median</th> \n",
       "        <th class=\"col_heading level0 col3\" >head_count</th> \n",
       "        <th class=\"col_heading level0 col4\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row0\" class=\"row_heading level0 row0\" >17</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow0_col0\" class=\"data row0 col0\" >shanghai</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow0_col1\" class=\"data row0 col1\" >16626</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow0_col2\" class=\"data row0 col2\" >15000</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow0_col3\" class=\"data row0 col3\" >25888</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow0_col4\" class=\"data row0 col4\" >18.55%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row1\" class=\"row_heading level0 row1\" >19</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow1_col0\" class=\"data row1 col0\" >shenzhen</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow1_col1\" class=\"data row1 col1\" >15631</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow1_col2\" class=\"data row1 col2\" >14000</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow1_col3\" class=\"data row1 col3\" >20757</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow1_col4\" class=\"data row1 col4\" >14.87%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row2\" class=\"row_heading level0 row2\" >8</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow2_col0\" class=\"data row2 col0\" >guangzhou</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow2_col1\" class=\"data row2 col1\" >13032</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow2_col2\" class=\"data row2 col2\" >12000</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow2_col3\" class=\"data row2 col3\" >17068</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow2_col4\" class=\"data row2 col4\" >12.23%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row3\" class=\"row_heading level0 row3\" >0</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow3_col0\" class=\"data row3 col0\" >beijing</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow3_col1\" class=\"data row3 col1\" >17453</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow3_col2\" class=\"data row3 col2\" >15000</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow3_col3\" class=\"data row3 col3\" >13823</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow3_col4\" class=\"data row3 col4\" >9.90%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row4\" class=\"row_heading level0 row4\" >9</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow4_col0\" class=\"data row4 col0\" >hangzhou</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow4_col1\" class=\"data row4 col1\" >14977</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow4_col2\" class=\"data row4 col2\" >12500</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow4_col3\" class=\"data row4 col3\" >8690</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow4_col4\" class=\"data row4 col4\" >6.23%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row5\" class=\"row_heading level0 row5\" >21</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow5_col0\" class=\"data row5 col0\" >wuhan</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow5_col1\" class=\"data row5 col1\" >11074</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow5_col2\" class=\"data row5 col2\" >10417</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow5_col3\" class=\"data row5 col3\" >8027</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow5_col4\" class=\"data row5 col4\" >5.75%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row6\" class=\"row_heading level0 row6\" >14</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow6_col0\" class=\"data row6 col0\" >nanjing</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow6_col1\" class=\"data row6 col1\" >12874</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow6_col2\" class=\"data row6 col2\" >12500</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow6_col3\" class=\"data row6 col3\" >7091</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow6_col4\" class=\"data row6 col4\" >5.08%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row7\" class=\"row_heading level0 row7\" >3</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow7_col0\" class=\"data row7 col0\" >chengdu</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow7_col1\" class=\"data row7 col1\" >11896</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow7_col2\" class=\"data row7 col2\" >11500</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow7_col3\" class=\"data row7 col3\" >7028</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow7_col4\" class=\"data row7 col4\" >5.04%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row8\" class=\"row_heading level0 row8\" >22</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow8_col0\" class=\"data row8 col0\" >xian</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow8_col1\" class=\"data row8 col1\" >11075</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow8_col2\" class=\"data row8 col2\" >10000</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow8_col3\" class=\"data row8 col3\" >3833</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow8_col4\" class=\"data row8 col4\" >2.75%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row9\" class=\"row_heading level0 row9\" >2</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow9_col0\" class=\"data row9 col0\" >changsha</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow9_col1\" class=\"data row9 col1\" >10847</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow9_col2\" class=\"data row9 col2\" >10000</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow9_col3\" class=\"data row9 col3\" >3354</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow9_col4\" class=\"data row9 col4\" >2.40%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row10\" class=\"row_heading level0 row10\" >11</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow10_col0\" class=\"data row10 col0\" >hefei</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow10_col1\" class=\"data row10 col1\" >9252</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow10_col2\" class=\"data row10 col2\" >8500</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow10_col3\" class=\"data row10 col3\" >3071</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow10_col4\" class=\"data row10 col4\" >2.20%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row11\" class=\"row_heading level0 row11\" >5</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow11_col0\" class=\"data row11 col0\" >dalian</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow11_col1\" class=\"data row11 col1\" >10030</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow11_col2\" class=\"data row11 col2\" >9000</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow11_col3\" class=\"data row11 col3\" >2889</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow11_col4\" class=\"data row11 col4\" >2.07%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row12\" class=\"row_heading level0 row12\" >4</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow12_col0\" class=\"data row12 col0\" >chongqing</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow12_col1\" class=\"data row12 col1\" >10017</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow12_col2\" class=\"data row12 col2\" >9000</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow12_col3\" class=\"data row12 col3\" >2570</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow12_col4\" class=\"data row12 col4\" >1.84%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row13\" class=\"row_heading level0 row13\" >23</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow13_col0\" class=\"data row13 col0\" >zhengzhou</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow13_col1\" class=\"data row13 col1\" >8348</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow13_col2\" class=\"data row13 col2\" >7000</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow13_col3\" class=\"data row13 col3\" >2317</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow13_col4\" class=\"data row13 col4\" >1.66%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row14\" class=\"row_heading level0 row14\" >7</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow14_col0\" class=\"data row14 col0\" >fuzhou</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow14_col1\" class=\"data row14 col1\" >10062</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow14_col2\" class=\"data row14 col2\" >9000</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow14_col3\" class=\"data row14 col3\" >2085</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow14_col4\" class=\"data row14 col4\" >1.49%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row15\" class=\"row_heading level0 row15\" >6</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow15_col0\" class=\"data row15 col0\" >dongguan</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow15_col1\" class=\"data row15 col1\" >11353</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow15_col2\" class=\"data row15 col2\" >10417</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow15_col3\" class=\"data row15 col3\" >1632</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow15_col4\" class=\"data row15 col4\" >1.17%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row16\" class=\"row_heading level0 row16\" >15</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow16_col0\" class=\"data row16 col0\" >ningbo</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow16_col1\" class=\"data row16 col1\" >10809</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow16_col2\" class=\"data row16 col2\" >10000</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow16_col3\" class=\"data row16 col3\" >1485</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow16_col4\" class=\"data row16 col4\" >1.06%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row17\" class=\"row_heading level0 row17\" >12</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow17_col0\" class=\"data row17 col0\" >jinan</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow17_col1\" class=\"data row17 col1\" >9375</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow17_col2\" class=\"data row17 col2\" >8500</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow17_col3\" class=\"data row17 col3\" >1479</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow17_col4\" class=\"data row17 col4\" >1.06%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row18\" class=\"row_heading level0 row18\" >18</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow18_col0\" class=\"data row18 col0\" >shenyang</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow18_col1\" class=\"data row18 col1\" >7851</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow18_col2\" class=\"data row18 col2\" >7000</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow18_col3\" class=\"data row18 col3\" >1452</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow18_col4\" class=\"data row18 col4\" >1.04%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row19\" class=\"row_heading level0 row19\" >16</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow19_col0\" class=\"data row19 col0\" >qingdao</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow19_col1\" class=\"data row19 col1\" >9549</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow19_col2\" class=\"data row19 col2\" >8750</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow19_col3\" class=\"data row19 col3\" >1385</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow19_col4\" class=\"data row19 col4\" >0.99%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row20\" class=\"row_heading level0 row20\" >20</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow20_col0\" class=\"data row20 col0\" >tianjin</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow20_col1\" class=\"data row20 col1\" >10988</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow20_col2\" class=\"data row20 col2\" >10000</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow20_col3\" class=\"data row20 col3\" >1147</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow20_col4\" class=\"data row20 col4\" >0.82%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row21\" class=\"row_heading level0 row21\" >13</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow21_col0\" class=\"data row21 col0\" >kuming</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow21_col1\" class=\"data row21 col1\" >8458</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow21_col2\" class=\"data row21 col2\" >8000</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow21_col3\" class=\"data row21 col3\" >1011</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow21_col4\" class=\"data row21 col4\" >0.72%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row22\" class=\"row_heading level0 row22\" >10</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow22_col0\" class=\"data row22 col0\" >harbin</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow22_col1\" class=\"data row22 col1\" >6403</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow22_col2\" class=\"data row22 col2\" >5250</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow22_col3\" class=\"data row22 col3\" >870</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow22_col4\" class=\"data row22 col4\" >0.62%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031eflevel0_row23\" class=\"row_heading level0 row23\" >1</th> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow23_col0\" class=\"data row23 col0\" >changchun</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow23_col1\" class=\"data row23 col1\" >8580</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow23_col2\" class=\"data row23 col2\" >7000</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow23_col3\" class=\"data row23 col3\" >614</td> \n",
       "        <td id=\"T_e7175bcc_59bd_11e9_87d3_701ce71031efrow23_col4\" class=\"data row23 col4\" >0.44%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1f787d2add8>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_city.sort_values(by='head_count', ascending=False).style.format({\"percentage\":\"{:.2%}\",\"salary_mean\":\"{:.0f}\",\"salary_median\":\"{:.0f}\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 24 artists>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(data_city.city_, data_city.head_count)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 公司 Company"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 公司性质 Company Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"blank level0\" ></th> \n",
       "        <th class=\"col_heading level0 col0\" >company_type_</th> \n",
       "        <th class=\"col_heading level0 col1\" >salary_mean</th> \n",
       "        <th class=\"col_heading level0 col2\" >salary_median</th> \n",
       "        <th class=\"col_heading level0 col3\" >head_count</th> \n",
       "        <th class=\"col_heading level0 col4\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <th id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031eflevel0_row0\" class=\"row_heading level0 row0\" >9</th> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow0_col0\" class=\"data row0 col0\" >us_eu</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow0_col1\" class=\"data row0 col1\" >16553</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow0_col2\" class=\"data row0 col2\" >15000</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow0_col3\" class=\"data row0 col3\" >5289</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow0_col4\" class=\"data row0 col4\" >4.07%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031eflevel0_row1\" class=\"row_heading level0 row1\" >2</th> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow1_col0\" class=\"data row1 col0\" >foreign_rep</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow1_col1\" class=\"data row1 col1\" >16158</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow1_col2\" class=\"data row1 col2\" >15000</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow1_col3\" class=\"data row1 col3\" >108</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow1_col4\" class=\"data row1 col4\" >0.08%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031eflevel0_row2\" class=\"row_heading level0 row2\" >3</th> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow2_col0\" class=\"data row2 col0\" >listed</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow2_col1\" class=\"data row2 col1\" >14597</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow2_col2\" class=\"data row2 col2\" >12500</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow2_col3\" class=\"data row2 col3\" >12400</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow2_col4\" class=\"data row2 col4\" >9.55%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031eflevel0_row3\" class=\"row_heading level0 row3\" >7</th> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow3_col0\" class=\"data row3 col0\" >startup</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow3_col1\" class=\"data row3 col1\" >14408</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow3_col2\" class=\"data row3 col2\" >12500</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow3_col3\" class=\"data row3 col3\" >3221</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow3_col4\" class=\"data row3 col4\" >2.48%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031eflevel0_row4\" class=\"row_heading level0 row4\" >0</th> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow4_col0\" class=\"data row4 col0\" >foreign</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow4_col1\" class=\"data row4 col1\" >13904</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow4_col2\" class=\"data row4 col2\" >12500</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow4_col3\" class=\"data row4 col3\" >5830</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow4_col4\" class=\"data row4 col4\" >4.49%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031eflevel0_row5\" class=\"row_heading level0 row5\" >8</th> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow5_col0\" class=\"data row5 col0\" >state</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow5_col1\" class=\"data row5 col1\" >13819</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow5_col2\" class=\"data row5 col2\" >12500</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow5_col3\" class=\"data row5 col3\" >7478</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow5_col4\" class=\"data row5 col4\" >5.76%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031eflevel0_row6\" class=\"row_heading level0 row6\" >5</th> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow6_col0\" class=\"data row6 col0\" >private</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow6_col1\" class=\"data row6 col1\" >13359</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow6_col2\" class=\"data row6 col2\" >12500</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow6_col3\" class=\"data row6 col3\" >94473</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow6_col4\" class=\"data row6 col4\" >72.79%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031eflevel0_row7\" class=\"row_heading level0 row7\" >1</th> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow7_col0\" class=\"data row7 col0\" >foreign_gov</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow7_col1\" class=\"data row7 col1\" >13347</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow7_col2\" class=\"data row7 col2\" >11667</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow7_col3\" class=\"data row7 col3\" >18</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow7_col4\" class=\"data row7 col4\" >0.01%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031eflevel0_row8\" class=\"row_heading level0 row8\" >6</th> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow8_col0\" class=\"data row8 col0\" >public_institution</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow8_col1\" class=\"data row8 col1\" >13137</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow8_col2\" class=\"data row8 col2\" >11667</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow8_col3\" class=\"data row8 col3\" >841</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow8_col4\" class=\"data row8 col4\" >0.65%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031eflevel0_row9\" class=\"row_heading level0 row9\" >4</th> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow9_col0\" class=\"data row9 col0\" >non_profit</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow9_col1\" class=\"data row9 col1\" >10167</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow9_col2\" class=\"data row9 col2\" >10000</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow9_col3\" class=\"data row9 col3\" >139</td> \n",
       "        <td id=\"T_ea32492e_59bd_11e9_9ac6_701ce71031efrow9_col4\" class=\"data row9 col4\" >0.11%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1f78b1bb898>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_company_type=get_sub_stats(data,'company_type_')\n",
    "data_company_type.style.format({\"percentage\":\"{:.2%}\",\"salary_mean\":\"{:.0f}\",\"salary_median\":\"{:.0f}\"})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "us_eu是欧美外企，startup是创业公司，listed是上市公司，state是国企，private是私企，foreign是非欧美外企，其他不足1000个样本的不管了。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "salary_us_eu=data[data.company_type_us_eu==1].monthly_salary\n",
    "salary_startup=data[data.company_type_startup==1].monthly_salary\n",
    "salary_listed=data[data.company_type_listed==1].monthly_salary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "F_onewayResult(statistic=119.77184496249959, pvalue=1.0851072054106644e-27)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.f_oneway(salary_us_eu,salary_startup)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "F_onewayResult(statistic=230.18298018979925, pvalue=1.1499907691025375e-51)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats.f_oneway(salary_us_eu,salary_listed)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由上报可知，欧美外企的工资显著高于其他企业。比创业公司和上司公司足足高了2000元呀。要努力学好英语呀！\n",
    "\n",
    "顺便做个广告，大家如果想通过看美剧或者看英文书提高英语，可以上我的网站，美剧单词网。里面会把你不懂的单词列出来，你再去听美剧，听英语有声书（网站提供），就能听懂了。\n",
    "\n",
    "https://www.tvshowwords.com/\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 公司规模 Company Size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_ecd54af6_59bd_11e9_8430_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"blank level0\" ></th> \n",
       "        <th class=\"col_heading level0 col0\" >company_size_</th> \n",
       "        <th class=\"col_heading level0 col1\" >salary_mean</th> \n",
       "        <th class=\"col_heading level0 col2\" >salary_median</th> \n",
       "        <th class=\"col_heading level0 col3\" >head_count</th> \n",
       "        <th class=\"col_heading level0 col4\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <th id=\"T_ecd54af6_59bd_11e9_8430_701ce71031eflevel0_row0\" class=\"row_heading level0 row0\" >0</th> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow0_col0\" class=\"data row0 col0\" >10000</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow0_col1\" class=\"data row0 col1\" >19133</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow0_col2\" class=\"data row0 col2\" >15000</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow0_col3\" class=\"data row0 col3\" >5705</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow0_col4\" class=\"data row0 col4\" >4.10%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ecd54af6_59bd_11e9_8430_701ce71031eflevel0_row1\" class=\"row_heading level0 row1\" >4</th> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow1_col0\" class=\"data row1 col0\" >5000_10000</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow1_col1\" class=\"data row1 col1\" >15322</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow1_col2\" class=\"data row1 col2\" >13500</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow1_col3\" class=\"data row1 col3\" >2753</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow1_col4\" class=\"data row1 col4\" >1.98%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ecd54af6_59bd_11e9_8430_701ce71031eflevel0_row2\" class=\"row_heading level0 row2\" >1</th> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow2_col0\" class=\"data row2 col0\" >1000_5000</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow2_col1\" class=\"data row2 col1\" >15248</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow2_col2\" class=\"data row2 col2\" >13500</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow2_col3\" class=\"data row2 col3\" >17578</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow2_col4\" class=\"data row2 col4\" >12.64%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ecd54af6_59bd_11e9_8430_701ce71031eflevel0_row3\" class=\"row_heading level0 row3\" >5</th> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow3_col0\" class=\"data row3 col0\" >500_1000</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow3_col1\" class=\"data row3 col1\" >14714</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow3_col2\" class=\"data row3 col2\" >12500</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow3_col3\" class=\"data row3 col3\" >14103</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow3_col4\" class=\"data row3 col4\" >10.14%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ecd54af6_59bd_11e9_8430_701ce71031eflevel0_row4\" class=\"row_heading level0 row4\" >2</th> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow4_col0\" class=\"data row4 col0\" >150_500</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow4_col1\" class=\"data row4 col1\" >13620</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow4_col2\" class=\"data row4 col2\" >12500</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow4_col3\" class=\"data row4 col3\" >32541</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow4_col4\" class=\"data row4 col4\" >23.40%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ecd54af6_59bd_11e9_8430_701ce71031eflevel0_row5\" class=\"row_heading level0 row5\" >6</th> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow5_col0\" class=\"data row5 col0\" >50_150</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow5_col1\" class=\"data row5 col1\" >12902</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow5_col2\" class=\"data row5 col2\" >12000</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow5_col3\" class=\"data row5 col3\" >42630</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow5_col4\" class=\"data row5 col4\" >30.65%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ecd54af6_59bd_11e9_8430_701ce71031eflevel0_row6\" class=\"row_heading level0 row6\" >3</th> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow6_col0\" class=\"data row6 col0\" >50</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow6_col1\" class=\"data row6 col1\" >12288</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow6_col2\" class=\"data row6 col2\" >11500</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow6_col3\" class=\"data row6 col3\" >23762</td> \n",
       "        <td id=\"T_ecd54af6_59bd_11e9_8430_701ce71031efrow6_col4\" class=\"data row6 col4\" >17.09%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1f78e7180b8>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_company_size=get_sub_stats(data,'company_size_')\n",
    "data_company_size.style.format({\"percentage\":\"{:.2%}\",\"salary_mean\":\"{:.0f}\",\"salary_median\":\"{:.0f}\"})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "公司越大，工资越高"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 行业 Industry"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style>  \n",
       "<table id=\"T_ee764028_59bd_11e9_b49e_701ce71031ef\" > \n",
       "<thead>    <tr> \n",
       "        <th class=\"blank level0\" ></th> \n",
       "        <th class=\"col_heading level0 col0\" >industry_</th> \n",
       "        <th class=\"col_heading level0 col1\" >salary_mean</th> \n",
       "        <th class=\"col_heading level0 col2\" >salary_median</th> \n",
       "        <th class=\"col_heading level0 col3\" >head_count</th> \n",
       "        <th class=\"col_heading level0 col4\" >percentage</th> \n",
       "    </tr></thead> \n",
       "<tbody>    <tr> \n",
       "        <th id=\"T_ee764028_59bd_11e9_b49e_701ce71031eflevel0_row0\" class=\"row_heading level0 row0\" >4</th> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow0_col0\" class=\"data row0 col0\" >finance</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow0_col1\" class=\"data row0 col1\" >15934</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow0_col2\" class=\"data row0 col2\" >14583</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow0_col3\" class=\"data row0 col3\" >5586</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow0_col4\" class=\"data row0 col4\" >3.33%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ee764028_59bd_11e9_b49e_701ce71031eflevel0_row1\" class=\"row_heading level0 row1\" >2</th> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow1_col0\" class=\"data row1 col0\" >edu</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow1_col1\" class=\"data row1 col1\" >15066</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow1_col2\" class=\"data row1 col2\" >12500</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow1_col3\" class=\"data row1 col3\" >10084</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow1_col4\" class=\"data row1 col4\" >6.01%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ee764028_59bd_11e9_b49e_701ce71031eflevel0_row2\" class=\"row_heading level0 row2\" >6</th> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow2_col0\" class=\"data row2 col0\" >logistic</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow2_col1\" class=\"data row2 col1\" >14341</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow2_col2\" class=\"data row2 col2\" >12500</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow2_col3\" class=\"data row2 col3\" >2268</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow2_col4\" class=\"data row2 col4\" >1.35%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ee764028_59bd_11e9_b49e_701ce71031eflevel0_row3\" class=\"row_heading level0 row3\" >9</th> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow3_col0\" class=\"data row3 col0\" >service</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow3_col1\" class=\"data row3 col1\" >14236</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow3_col2\" class=\"data row3 col2\" >12500</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow3_col3\" class=\"data row3 col3\" >1432</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow3_col4\" class=\"data row3 col4\" >0.85%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ee764028_59bd_11e9_b49e_701ce71031eflevel0_row4\" class=\"row_heading level0 row4\" >1</th> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow4_col0\" class=\"data row4 col0\" >computer</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow4_col1\" class=\"data row4 col1\" >13756</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow4_col2\" class=\"data row4 col2\" >12500</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow4_col3\" class=\"data row4 col3\" >119772</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow4_col4\" class=\"data row4 col4\" >71.33%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ee764028_59bd_11e9_b49e_701ce71031eflevel0_row5\" class=\"row_heading level0 row5\" >10</th> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow5_col0\" class=\"data row5 col0\" >trade</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow5_col1\" class=\"data row5 col1\" >13682</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow5_col2\" class=\"data row5 col2\" >12500</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow5_col3\" class=\"data row5 col3\" >11629</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow5_col4\" class=\"data row5 col4\" >6.93%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ee764028_59bd_11e9_b49e_701ce71031eflevel0_row6\" class=\"row_heading level0 row6\" >5</th> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow6_col0\" class=\"data row6 col0\" >gov</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow6_col1\" class=\"data row6 col1\" >13413</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow6_col2\" class=\"data row6 col2\" >12500</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow6_col3\" class=\"data row6 col3\" >3510</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow6_col4\" class=\"data row6 col4\" >2.09%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ee764028_59bd_11e9_b49e_701ce71031eflevel0_row7\" class=\"row_heading level0 row7\" >7</th> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow7_col0\" class=\"data row7 col0\" >medical</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow7_col1\" class=\"data row7 col1\" >12950</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow7_col2\" class=\"data row7 col2\" >12500</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow7_col3\" class=\"data row7 col3\" >4309</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow7_col4\" class=\"data row7 col4\" >2.57%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ee764028_59bd_11e9_b49e_701ce71031eflevel0_row8\" class=\"row_heading level0 row8\" >8</th> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow8_col0\" class=\"data row8 col0\" >realestate</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow8_col1\" class=\"data row8 col1\" >12855</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow8_col2\" class=\"data row8 col2\" >12000</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow8_col3\" class=\"data row8 col3\" >3122</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow8_col4\" class=\"data row8 col4\" >1.86%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ee764028_59bd_11e9_b49e_701ce71031eflevel0_row9\" class=\"row_heading level0 row9\" >3</th> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow9_col0\" class=\"data row9 col0\" >energy</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow9_col1\" class=\"data row9 col1\" >12729</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow9_col2\" class=\"data row9 col2\" >12000</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow9_col3\" class=\"data row9 col3\" >3178</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow9_col4\" class=\"data row9 col4\" >1.89%</td> \n",
       "    </tr>    <tr> \n",
       "        <th id=\"T_ee764028_59bd_11e9_b49e_701ce71031eflevel0_row10\" class=\"row_heading level0 row10\" >0</th> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow10_col0\" class=\"data row10 col0\" >ads</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow10_col1\" class=\"data row10 col1\" >12515</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow10_col2\" class=\"data row10 col2\" >11500</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow10_col3\" class=\"data row10 col3\" >3034</td> \n",
       "        <td id=\"T_ee764028_59bd_11e9_b49e_701ce71031efrow10_col4\" class=\"data row10 col4\" >1.81%</td> \n",
       "    </tr></tbody> \n",
       "</table> "
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x1f790904240>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_industry=get_sub_stats(data,'industry_')\n",
    "data_industry.style.format({\"percentage\":\"{:.2%}\",\"salary_mean\":\"{:.0f}\",\"salary_median\":\"{:.0f}\"})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "金融业果然是工资最高的。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "name": "python",
   "nbconvert_exporter": "python",
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